Transparent, Reproducible AI Tool for Health Information Analysis
Written by AZoRoboticsFeb 26 2021
Clinical research necessitates the mining of data to gain crucial insights. Machine learning, which involves developing algorithms to identify patterns, finds it hard to do this in the case of data related to health records since information of this kind is neither static nor collected regularly.
Prof. Jeremy Weiss, an expert in machine learning and healthcare informatics. Image Credit: Carnegie Melon University Heinz College.
As part of a new study, researchers have developed a transparent, reproducible machine learning tool to allow the analysis of health information. The tool can be employed in clinical forecasting, which can estimate trends and outcomes in individual patients.
Penn State’s Student Programming Association (SPA) hosted actor and singer Leslie Odom Jr. for a virtual lecture Friday evening.
Throughout it, Odom discussed everything from his time in the award-winning musical “Hamilton” to his experiences overcoming stage fright.
The actor began by answering questions regarding what sparked his interest in performing. He said that early teachers and adults steered him toward the stage due to extra energy and fearlessness when it came to getting up in front of people.
Odom grew up in Philadelphia and wrote speeches that he delivered in citywide competitions. He credited those writing for helping him learn to stand up and communicate, and develop a point of view.